class_docstr: Construct a CoreML KNearestNeighborsClassifier specification.
  
  Please see the Core ML Nearest Neighbors protobuf message for more information
  on KNearestNeighborsClassifier parameters.
  
  Examples
  --------
  .. sourcecode:: python
  
      from coremltools.models.nearest_neighbors import KNearestNeighborsClassifierBuilder
      from coremltools.models.utils import save_spec
  
      # Create a KNearestNeighborsClassifier model that takes 4-dimensional input data and outputs a string label.
      >>> builder = KNearestNeighborsClassifierBuilder(input_name='input',
      ...                                              output_name='output',
      ...                                              number_of_dimensions=4,
      ...                                              default_class_label='default_label')
  
      # save the spec by the builder
      >>> save_spec(builder.spec, 'knnclassifier.mlmodel')
      
docstr: Get the license for the KNearestNeighborsClassifier model.
  
  Returns
  -------
  The license.
docstr_tok: ["Get","the","license","for","the","KNearestNeighborsClassifier","model",".","Returns","--","--","--","-","The","license","."]
code: def license(self):
      """
      Get the license for the KNearestNeighborsClassifier model.
  
      Returns
      -------
      The license.
      """
      return self.spec.description.metadata.license
  
imports: import numpy
  import coremltools
  from ...proto import FeatureTypes_pb2
  from ..None import datatypes
label_desc: Use image node_id 4 for calling the KNearestNeighborsClassifierBuilder obj's underlying member method code with example usage: obj.license() and returns: self